Combined Classifiers In Recognition Of Handwritten Kannada Numerals: A Hybrid Approach

Acharya, Dinesh U and Subbareddy , NV and Makkithaya, Krishnamoorthi (2009) Combined Classifiers In Recognition Of Handwritten Kannada Numerals: A Hybrid Approach. International Journal of Information Technology and Knowledge Management, 2 (2). pp. 305-311. ISSN 0973-4414

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The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals using both unsupervised and supervised classifiers. Four different types of structural features, namely, direction frequency code, water reservoir, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed. Combining classifiers has proved to be an effective solution to several classification problems in pattern recognition. In the image classification, it is often beneficial to consider each feature type separately, and to integrate the initial classification results by a final classifier. In this paper, we developed a robust hybrid approach where fuzzy k-Nearest Neighbor (fuzzy k-NN) and fuzzy c-means (FCM) as base classifiers for individual feature sets, the results of which together forms the feature vector for the final k-Nearest Neighbor (k-NN) classifier. Testing is done, using different feature sets, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the different existing methods.

Item Type: Article
Additional Information: Copyright © Serials Publications
Uncontrolled Keywords: Structural Features;Numeral Recognition;Fuzzy k Nearest Neighbor;Fuzzy c-means;Multiple Classifiers;Classification Result Vector
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Engineering > MIT Manipal > MCA
Depositing User: MIT Library
Date Deposited: 29 Apr 2011 11:09
Last Modified: 09 Jun 2011 06:18

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